CV

Lin Changxing

1729919327@qq.com
+86 15220464082
Guangzhou, Guangdong Province

Summary

硕士研究生,专注于计算机视觉(三维建模、目标检测、语义分割)和机器学习研究。拥有有限元与离散元仿真及嵌入式系统开发经验。导师为华南农业大学工学院杨丹彤教授。

Education

  • Agricultural Mechanical Engineering
    Present
    South China Agricultural University
    GPA: 3.6
  • Aerospace Manufacturing Engineering
    2023-07
    Beijing Institute of Technology Zhuhai College

Work Experience

  • Technical Support Intern
    2024-06 - 2024-12
    Zhongwang Discrete Element Simulation Technology
    Analyzed and reproduced complex simulation cases using ZWDEM and ZW3D software to diagnose functional issues and assist software improvements. Authored comprehensive technical documentation to streamline customer support, improving self-service capabilities for users of ZWDEM software.
  • Technical Support Intern
    2023-10 - 2024-04
    Altair Finite Element Structural Simulation (HyperMesh)
    Troubleshooted customer technical inquiries and delivered software training sessions, fostering user proficiency with the HyperWorks suite (HyperMesh, HyperView) and EDEM. Proficient in using the HyperWorks series of tools and EDEM for simulation technical support.
  • Part-time Counselor
    2023-09 - 2023-12
    Graduate School of South China Agricultural University

Skills

Image Processing

  • YOLO
  • DeepLab
  • 3DFlow
  • MeshLab
  • Photoshop
  • CapCut

Programming Languages

  • Python
  • C

Simulation Analysis

  • Finite Element Simulation (HyperMesh)
  • Discrete Element Simulation (EDEM/ZWDE)
  • Multibody Dynamics (Recurdyn)

CAD/Graphics Design Software

  • AutoCAD
  • ZWDE CAD
  • ZWDE 3D
  • CATIA
  • SolidWorks

Languages and Certifications

  • CET-6
  • BEC Business English Intermediate
  • IELTS (preparing)

Other

  • National Computer Level 2 Certificate
  • Motor Vehicle Driver's License (C1)

Publications

  • A method for detecting the impurity rate of cut sugarcane segments in drone-captured images, based on YOLOv8.
    Use Roboflow to calibrate and enhance the data, then perform target detection using an improved YOLOv8 architecture. Integrate the optimized model into the JETSON edge device, design the UI interface and develop a Python-based impurity rate calculation tool.
  • Subsequent supplements
    This section includes ongoing research and manuscripts under preparation.